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github.com/AMAP-ML/Eevee
/ functions
Functions
226 in github.com/AMAP-ML/Eevee
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Functions
226
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Types & classes
53
↓ 1 callers
Method
unit_vace
(self, inputs)
models/pipeline.py:305
↓ 1 callers
Function
unpatchify
(x, patch_size)
models/vae.py:214
↓ 1 callers
Method
vace
(self, inputs)
models/training.py:162
↓ 1 callers
Method
vae_output_to_image
(self, vae_output, pattern="B C H W", min_value=-1, max_value=1)
models/pipeline.py:185
↓ 1 callers
Method
vae_output_to_video
(self, vae_output, pattern="B C T H W", min_value=-1, max_value=1)
models/pipeline.py:178
Method
__call__
( self, prompt, negative_prompt, vace_video = None, vace_video_mask= N
models/pipeline.py:197
Method
__call__
(self, sequence, **kwargs)
models/prompter.py:84
Method
__del__
(self)
test/test.py:19
Method
__del__
(self)
test/test.py:69
Method
__getitem__
(self, data_id)
dataset/eevee_dataset.py:36
Method
__getitem__
(self, item)
test/test.py:16
Method
__init__
(self, output_path, remove_prefix_in_ckpt=None, state_dict_converter=lambda x:x)
utils/logger.py:4
Method
__init__
( self, dresses_dataset_base_path = None, dresses_dataset_metadata_path = None,
dataset/eevee_dataset.py:7
Method
__init__
(self, file_name)
test/test.py:10
Method
__init__
(self, video_file=None, image_folder=None, height=None, width=None, **kwargs)
test/test.py:23
Method
__init__
( self, num_inference_steps = 100, num_train_timesteps = 1000, shift = 3.0,
models/scheduler.py:5
Method
__init__
(self, *args, **kwargs)
models/vae.py:38
Method
__init__
(self, dim, channel_first=True, images=True, bias=False)
models/vae.py:57
Method
__init__
(self, dim, mode)
models/vae.py:84
Method
__init__
(self, dim, mode)
models/vae.py:229
Method
__init__
(self, in_dim, out_dim, dropout=0.0)
models/vae.py:269
Method
__init__
(self, dim)
models/vae.py:309
Method
__init__
( self, in_channels, out_channels, factor_t, factor_s=1, )
models/vae.py:346
Method
__init__
( self, in_dim, out_dim, dropout, mult, temperal_downsample=False, down_flag=False )
models/vae.py:443
Method
__init__
( self, in_dim, out_dim, dropout, mult, temperal_upsample=False, up_flag=False )
models/vae.py:478
Method
__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
models/vae.py:519
Method
__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
models/vae.py:622
Method
__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
models/vae.py:738
Method
__init__
(self, dim=128, z_dim=4, dim_mult=[1, 2, 4, 4],
models/vae.py:844
Method
__init__
(self, dim=96, z_dim=16, dim_mult=[1, 2, 4, 4],
models/vae.py:953
Method
__init__
(self, z_dim=16)
models/vae.py:1060
Method
__init__
(self)
models/vae.py:1257
Method
__init__
(self, dim=160, z_dim=48, dec_dim=256, dim
models/vae.py:1271
Method
__init__
(self, z_dim=48, dim=160)
models/vae.py:1356
Method
__init__
( self, device = "cuda", torch_dtype = torch.bfloat16, height_division_factor
models/pipeline.py:15
Method
__init__
(self, device="cpu", torch_dtype=torch.float32)
models/pipeline.py:396
Method
__init__
( self, vae_model_path = None, # text_encoder_model_path = No
models/training.py:9
Method
__init__
(self, dim, eps=1e-5)
models/dit.py:124
Method
__init__
(self, num_heads)
models/dit.py:138
Method
__init__
(self, dim: int, num_heads: int, eps: float = 1e-6)
models/dit.py:148
Method
__init__
(self, dim: int, num_heads: int, eps: float = 1e-6, has_image_input: bool = False)
models/dit.py:174
Method
__init__
(self,)
models/dit.py:213
Method
__init__
(self, has_image_input: bool, dim: int, num_heads: int, ffn_dim: int, eps: float = 1e-6)
models/dit.py:220
Method
__init__
(self, dim: int, out_dim: int, patch_size: Tuple[int, int, int], eps: float)
models/dit.py:277
Method
__init__
( self, dim: int, in_dim: int, ffn_dim: int, out_dim: int, tex
models/dit.py:296
Method
__init__
(self)
models/dit.py:437
Method
__init__
( self, torch_dtype = torch.float16, device = "cuda", )
models/manager.py:112
Method
__init__
(self, has_image_input, dim, num_heads, ffn_dim, eps=1e-6, block_id=0)
models/vace.py:28
Method
__init__
(self)
models/vace.py:117
Method
__init__
(self)
models/prompter.py:14
Method
__init__
(self, name, seq_len=None, clean=None, **kwargs)
models/prompter.py:74
Method
__init__
(self, tokenizer_path=None, text_len=512)
models/prompter.py:122
Method
__init__
(self, dim, dim_attn, num_heads, dropout=0.1)
models/text_encoder.py:40
Method
__init__
(self, dim, dim_ffn, dropout=0.1)
models/text_encoder.py:94
Method
__init__
(self, dim, dim_attn, dim_ffn, num_heads,
models/text_encoder.py:115
Method
__init__
(self, num_buckets, num_heads, bidirectional, max_dist=128)
models/text_encoder.py:149
Method
__init__
(self, vocab=256384, dim=4096, dim_attn=4096,
models/text_encoder.py:211
Method
__init__
(self)
models/text_encoder.py:262
Method
__len__
(self)
dataset/eevee_dataset.py:60
Method
__len__
(self)
test/test.py:13
Function
block_causal_mask
(x, block_size)
models/vae.py:19
Method
create_custom_forward
(module)
models/dit.py:404
Method
create_custom_forward
(module)
models/vace.py:87
Function
custom_forward
(*inputs)
models/pipeline.py:374
Method
custom_forward
(*inputs)
models/dit.py:405
Method
custom_forward
(*inputs)
models/vace.py:88
Method
decode
(self, hidden_states, device, tiled=False, tile_size=(34, 34), tile_stride=(18, 16))
models/vae.py:1235
Method
decode
(self, z, scale)
models/vae.py:1326
Method
encode
(self, videos, device, tiled=False, tile_size=(34, 34), tile_stride=(18, 16))
models/vae.py:1218
Method
encode
(self, x, scale)
models/vae.py:1298
Method
extend_prompt
(self, prompt:str, positive=True)
models/prompter.py:40
Method
forward
(self, x, cache_x=None)
models/vae.py:44
Method
forward
(self, x)
models/vae.py:67
Method
forward
Fix bfloat16 support for nearest neighbor interpolation.
models/vae.py:75
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:120
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:283
Method
forward
(self, x)
models/vae.py:321
Method
forward
(self, x: torch.Tensor)
models/vae.py:363
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:469
Method
forward
(self, x, feat_cache=None, feat_idx=[0], first_chunk=False)
models/vae.py:506
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:569
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:679
Method
forward
(self, x, feat_cache=None, feat_idx=[0])
models/vae.py:789
Method
forward
(self, x, feat_cache=None, feat_idx=[0], first_chunk=False)
models/vae.py:889
Method
forward
(self, x)
models/vae.py:978
Method
forward
(self, data)
models/training.py:50
Method
forward
(self, x)
models/dit.py:132
Method
forward
(self, q, k, v)
models/dit.py:142
Method
forward
(self, x, freqs)
models/dit.py:163
Method
forward
(self, x: torch.Tensor, y: torch.Tensor)
models/dit.py:194
Method
forward
(self, x, gate, residual)
models/dit.py:216
Method
forward
(self, x, context, t_mod, freqs)
models/dit.py:237
Method
forward
(self, x)
models/dit.py:270
Method
forward
(self, x, t_mod)
models/dit.py:285
Method
forward
(self, x: torch.Tensor, timestep: torch.Tensor, context: torch
models/dit.py:376
Method
forward
(self, c, x, context, t_mod, freqs)
models/vace.py:35
Method
forward
(self, x)
models/text_encoder.py:17
Method
forward
(self, x)
models/text_encoder.py:30
Method
forward
x: [B, L1, C]. context: [B, L2, C] or None. mask: [B, L2] or [B, L1, L2] or None.
models/text_encoder.py:55
Method
forward
(self, x)
models/text_encoder.py:105
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